Comparing the Relative Fit of Various Factor Models of the Self-Consciousness Scale in Two Independent Samples
Bibliographic record
Abstract
Research shows that using highly self-aware participants yields studies of higher reliability, validity, and statistical power; dispositional self-awareness is commonly measured using the Fenigstein Self-Consciousness Scale (Fenigstein, Scheier, & Buss, 1975). This study used confirmatory factor analysis to compare various factor models that may underlie that scale. Two independent student samples (296 from Bernstein, Teng, & Garbin, 1986, and 350 from a large Canadian university) completed the scale. Using 6 fit criteria, results from both samples supported the Burnkrant and Page (1984) 4-factor model, namely, that self-consciousness consists of 3 principle scales: Social Anxiety, Public Self-Consciousness, and Private Self-Consciousness (divided into Internal State Awareness and Self-Reflectiveness). We discuss the psychometric implications of enhancing scale reliability, validity, and self-awareness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.056 | 0.174 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".